Zhaofei Yu

Electrical and Electronic Engineering · 2020–2023

A researcher in the Science corpus: 3 papers; trusts 50 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Electrical and Electronic Engineering — 83 citations into it; #14,964 of 16,539 by trust here, #10,998 by citations
• Cognitive Neuroscience — 78 citations into it; #9,975 of 10,852 by trust here, #7,130 by citations
• Artificial Intelligence — 60 citations into it
• Computer Vision and Pattern Recognition — 35 citations into it
• Cellular and Molecular Neuroscience — 32 citations into it
• Model Architectures — 24 citations into it
• Optimization & Training — 15 citations into it

Whom Zhaofei Yu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Kaiming He
3. Yann LeCun
4. Sergey Ioffe
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Diederik P. Kingma
8. Yujie Wu
9. Christian Szegedy
10. Hesham Mostafa

Who trusts Zhaofei Yu overall

1. Man Yao

Papers from Zhaofei Yu's perspective

Ordered by how strongly the researchers Zhaofei Yu trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Going deeper with convolutions
7. ImageNet Large Scale Visual Recognition Challenge
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Deep Residual Learning in Spiking Neural Networks (2021) — 793 citations
• Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks (2020) — 776 citations
• SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence (2023) — 522 citations